Investigating relationships between albacore tuna (Thunnus alalunga) CPUE and prey distribution in the Bay of Biscay

Progress in Oceanography 86 (2010) 105–114

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Investigating relationships between albacore tuna (Thunnus alalunga) CPUE and prey distribution in the Bay of Biscay Ainhoa Lezama-Ochoa a,*, Guillermo Boyra a, Nicolas Goñi a, Haritz Arrizabalaga a, Arnaud Bertrand b a b

AZTI-Tecnalia, Marine Research Unit, Herrera Kaia Portualdea z/g, 20110 Pasaia, Basque Country, Spain Institut de Recherche pour le développement (IRD), CRH, Avenue Jean Monnet, BP 171, 34203 Sète, Cedex, France

a r t i c l e

i n f o

Article history: Received 14 March 2008 Received in revised form 25 August 2009 Accepted 10 April 2010 Available online 28 April 2010

a b s t r a c t The Bay of Biscay in the northeast Atlantic is an important feeding zone for juvenile albacore tuna (Thunnus alalunga) during their summer migration northwards. Spatial distribution and abundance of their potential prey [planktonic organisms, anchovy (Engraulis encrasicolus) and other small pelagics] were investigated in the southeast Bay of Biscay during acoustic surveys in autumn from 2003 to 2005. The relationships between albacore tuna catch per unit of effort (CPUE), and prey abundance and sea surface temperature (SST) were studied at different spatiotemporal scales. We observed positive and significant correlations between albacore tuna CPUE and anchovy abundance and total prey abundance, at different spatial scales. However, in 2003, a year characterised by extreme temperatures compared to the other years of this study, the relationship between CPUE and prey abundance was much weaker. Instead, we found a significant negative correlation with SST. Ó 2010 Elsevier Ltd. All rights reserved.

1. Introduction Ecological systems exhibit heterogeneity over a broad range of scales, with marine organisms having an aggregated, patchy distribution on a wide variety of space and time scales from centimetres to thousands of kilometres (Wiebe, 1970; Steele, 1976; Haury et al., 1978; Mackas and Boyd, 1979; Mackas et al., 1985; Frontier, 1987; Russel et al., 1992; Davis et al., 1991; Bertrand et al., 2002b). Studying interactions between predator and prey implies choosing an appropriate space–time scale. This choice is difficult because populations and ecosystems cannot be described at a single scale (Levin, 1992). Processes at regional scales are more regular; its study being key to our understanding of trophic interactions among populations (Rose and Leggett, 1990). The relationships between tuna and their prey are generally studied at regional (1000s of km), meso (100s of km) and local (km) scales (Josse et al., 1998; Bertrand, 1999; Bertrand et al., 2002b; Goñi et al., 2009). The range of tuna distribution is known to be limited mainly due to hydrological conditions (Sharp, 1978; Sund et al., 1981; Brill, 1994; Bard, 2001; Bertrand et al., 2002a,b); however, within areas of suitable abiotic conditions, tuna tend to be more abundant where prey are concentrated (Sund et al., 1981; Roger, 1994; Bertrand, 1999; Bertrand et al., 2002b). Every summer, albacore tuna (Thunnus alalunga) perform seasonal feeding migrations into the Bay of Biscay. This area consti* Corresponding author. Tel.: +34 943 004 800; fax: +34 943 004 801. E-mail address: [email protected] (A. Lezama-Ochoa). 0079-6611/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.pocean.2010.04.006

tutes a hot spot for juvenile tuna in search of prey and sustains a traditional seasonal fishery, targeting albacore tuna from June to October. Catches occur off the shelf (but adjacent to the shelf break) from the Cantabric Coast (Fig. 1) up to 48°N (Santiago, 2004). So far, no effort has been put into producing combined studies of the spatial distribution of albacore tuna catches and their potential prey, predominantly small pelagic fish and euphausiids (Goñi, 2008). Since 2003, annual acoustic surveys are undertaken, in autumn, in the Bay of Biscay (JUVENA Program, Boyra and Uriarte, 2006; Boyra et al., 2006). Although these surveys are executed to assess the abundance of juvenile anchovy and are under constraints imposed by management requirements, they partially overlap with the period and location of the albacore tuna baitboat and trolling fishing season in the Bay of Biscay. This makes JUVENA an important source of information, with acoustic data as a key tool, for the observation of the distribution and spatial–temporal structure of the pelagic community in the area. The aim of this study was to examine how the spatial distribution and abundance of albacore tuna prey impact CPUE in the Bay of Biscay. Data come from the annual acoustic surveys (2003– 2005) and CPUE logbook records from commercial fisheries. We used the description of interannual variation in the patterns of spatial distribution of small pelagic fish and euphausiids abundance as an indicator of food availability for albacore tuna. The relationships between presence and abundance of prey and albacore tuna were examined at both regional (study area) and local (44, 56 and 111 km) scales.

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Fig. 1. Overview of the study area and theoretical sampling design. The scheme shows vertical (V), horizontal (H) and diagonal (H) transects, perpendicular to the coastline. The dotted line represents the minimum area covered throughout all years of the study.

2. Materials and methods 2.1. Data acquisition 2.1.1. Albacore CPUE data Daily catch rates of albacore tuna were obtained from the logbooks distributed in albacore tuna baitboat and trolling fisheries. The logbooks provided the following information on a daily basis: name of vessel, date and location (latitude and longitude) of the fishing set, number of specimens captured according to commercial category, type of bait used and sea surface temperature (SST). 2.1.2. Acoustic surveys Information on tuna prey abundance and distribution were obtained from three acoustic surveys performed within the JUVENA program in the Bay of Biscay (Fig. 1) from 2003 to 2005 (Boyra and Uriarte, 2006; Boyra et al., 2006). These surveys lasted about 25 days from late September to early October and were performed using a 35-m commercial vessel. The sampling strategy was designed to monitor anchovy and other small pelagic fish, taking into account information collected from the Spanish live-bait tuna fishery that traditionally target juvenile anchovy. During this season, juvenile anchovy are generally observed crossing the continental shelf on their way to the coast from offshore waters (Uriarte et al., 2001). The survey design was a combination of systematic and adaptive schemes. The systematic scheme was based on cross-shelf transect lines from the coast (20 m bottom depth) to beyond the shelf break. Transects were parallel, regularly spaced and perpendicular to the coast with an inter-transect distance of 17.5 nautical miles (Fig. 1). Standard transects ranged 6–10 miles off the shelf. Transects were prolonged as long as fish were detected and then

stopped when more than 6 nautical miles were covered without encountering any fish schools. Such an adaptive scheme was adopted to ensure the complete coverage of the extension area of juvenile anchovy. Acoustic data were recorded with 38 and 120-kHz Simrad EY60 split-beam, scientific echosounders (Kongsberg Simrad AS, Kongsberg, Norway). The water column was sampled to depths of 200 m. Acoustic back-scattered energy by surface unit (sA, MacLennan et al., 2002) was recorded for each geo-referenced nautical mile (1852 m). Acoustic sampling was performed during daytime, when juvenile anchovy aggregate in schools (Uriarte et al., 2001) and can be easily distinguished from zooplankton structures. The identification of organisms and population size structure was obtained from net sampling and echo trace characteristics (Boyra and Uriarte, 2006; Boyra et al., 2006). Zooplankton (mainly euphausiids) were sampled from purse-seine nets and in some cases zooplankton nets. Sampling was not systematic and we obtained only casual identifications on purse-seine nets (grid-size 0.5–0.8 cm, suitable for juvenile anchovy) or by vertical plankton haul, using a 150lm PairoVET net (2-CalVET nets, Smith et al., 1985). Furthermore, sampling of plankton nets was only performed during the daytime, which is the period when euphausiids are distributed in midwater. Finally, oceanographic data were collected from the water column at 60 stations using a CTD profiler, but only SST was considered in this work (Figs. 2–4). 2.2. Acoustic data processing Acoustic records were processed using Movies+ software (Weill et al., 1993). Acoustic echoes were identified according to both bifrequency analysis and information obtained from net sampling. Bi-frequency analysis uses the response of different targets as op-

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Fig. 2. Spatial distribution of albacore CPUE (empty circles) and (a) anchovy (full grey circles), (b) fluid-like (full grey circles), (c) other pelagics (full grey circles), and (d) SST (in °C), during 2003. In all subplots, the dotted line shows the area covered during this year.

posed to the different operative frequencies to distinguish among taxonomic groups. The different frequency responses between swimbladdered fish (e.g. anchovy) and fluid-like planktonic organisms (Stanton et al., 1994) like crustacean zooplankton (e.g. euphausiids) is particularly well established (Madureira et al., 1993a,b; Kang et al., 2002; Simmonds and MacLennan, 2005). The energy scattered by a given target, at both 38 and 120 kHz, is compared on a ‘‘pixel by pixel” basis (our acoustic pixels are one ping long and 19.2 cm high), to create different filtering masks, each suited for the discrimination of a single taxonomic group. The masks are applied to the echograms, to obtain virtual channels that contain, ideally, energy attributed only to the corresponding taxonomic group. The mask for fish was obtained by creating a new channel with the subtraction, pixel by pixel, of the 38 kHz from the 120 kHz channel. Subsequently, a constant value of 55 dB was added to this new channel and, finally, a 55 dB threshold was applied.

The resulting channel is a mask that is applied to the 38 kHz channel, leaving fish detections unaltered while removing other echoes. For fluid-like organisms, the procedure was similar. A new channel was created using an inverse subtraction since the response of fish and fluid-like organisms is inverse at these frequencies; i.e. (120–38 kHz) 55 dB. Once again, a 55 dB threshold was applied to establish the mask; this was applied, on this occasion, over the 120 kHz. With this method only fluid-like organisms observed at both 38 and 120 kHz can be assessed. The 38-kHz frequency does not allow the detection of small and weak targets and only targets with a size equivalent to a sphere of 1 mm can be fully detected (Mitson et al., 1996). This corresponds to organisms with a size larger than 3 mm. Data show that zooplankton species composition in the Bay of Biscay (Albaina and Irigoien, 2004, 2007), is predominantly euphausiids with a size larger than 3 mm. Therefore we can assume that the field ‘fluid-like organisms’ observed by acoustics is a proxy of euphausiids abundance.

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Fig. 3. Spatial distribution of albacore CPUE (empty circles) and (a) anchovy (full grey circles), (b) fluid-like (full grey circles), (c) other pelagics (full grey circles), and (d) SST (in °C), during 2004. In all subplots, the dotted line shows the area covered during this year.

Visual scrutinizing of the echograms by a human expert complemented the bi-frequency method used to distinguish among taxonomic groups along the echogram. Afterwards, the energy attributed to fish was further split into anchovy and ‘‘other pelagics” using the information obtained from fishing hauls. Once the energy was split into anchovy, other pelagics and fluid-like organisms, an automatic shoal detection routine was computed in Movies+ (Weill et al., 1993; Diner et al., 2006). Here, isolated shoal-type objects were identified and extracted from the echograms; measuring up to 40 characteristics to describe each shoal (Petitgas et al., 2001). Thresholds were applied for minimum school object length (5 m), height (0.5 m) (Petitgas, 2003) and average density (between 80 and 50 dB for fluid-like organisms, and 60 to 0 dB for fish). Extracted school objects with a length smaller than two beam widths at depth were rejected, since they are considered to be too small to be characterised adequately (Diner, 2001; Diner et al., 2006). Shoal objects between the surface and 5 m depth were also rejected to avoid the risk of confusion with echoes generated

by surface-related turbulence. Finally, the volume reverberation index of the shoal (Sv, MacLennan et al., 2002) was computed for three prey groups (anchovy, ‘‘other pelagics” and ‘‘fluid-like”). The relative abundance (within each Sprey group) of each shoal v (rag, in m2) was estimated as: area  10 10 , with area being the area of the vertical section of the shoal (Diner, 2001; Diner et al., 2006). 2.3. Data analysis With the adaptive scheme we used, the area covered by acoustic surveys was variable among years. Therefore we defined a different study area for each year in order to perform spatial analyses. The core of the study area was defined as the intersection between the area covered by the JUVENA surveys and the spatial distribution of the albacore tuna catches (generally off the continental shelf). This area was limited by the bathymetry of 150 m on the coastal side and the end of the sampled transects offshore (Figs. 2–4). Consequently, only albacore tuna catches made within

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Fig. 4. Spatial distribution of albacore CPUE (empty circles) and (a) anchovy (full grey circles), (b) fluid-like (full grey circles), (c) other pelagics (full grey circles), and (d) SST (in °C), during 2005. In all subplots, the dotted line shows the area covered during this year.

the yearly JUVENA spatiotemporal window of coverage and prey detected in waters deeper than 150 m were considered for analyses. Likewise, in order to relate CPUE to prey abundance at a regional scale, the relationship between overall prey abundance and albacore tuna CPUE was analyzed during this time series, distinguishing between CPUEs obtained inside and outside the JUVENA coverage area (Table 1). First, we performed interannual correlations (Pearson test) between the albacore CPUE (inside and outside the JUVENA area)

and abundance of prey (anchovy, other pelagics, fluid-like, and ‘‘total prey”, i.e. the sum of the prey) in the study area. We then investigated the relationships between albacore CPUE and prey at smaller spatial scales (111, 56, and 44-km diameter). It was not possible to accurately work at a smaller scale because of the inter-transect distance (32.4 km) and the rather low number of CPUE data (Table 1). From a temporal point of view, we defined a time lag that increases together with the spatial grid; i.e. scale 1: 0.40 degrees (44 km) – 6 days; scale 2: 0.50 degree (56 km) – 8 days;

Table 1 Interannual variation of abundance (m2) for three groups of prey and its relationship with CPUE (number of tuna/day) located inside and outside the area of study, for 3 years of study. Year

Total CPUE

CPUE inside

CPUE outside

Anchovy abundance

Pelagics abundance

Fluid-like plankton abundance

2003 2004 2005

103 182 130

58 6 110

45 176 20

65.858 0.001 101.925

48.16 16.58 64.46

0.101 4.946 15.709

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and scale 3: 1 degree (111 km) – 10 days. In this case the central point was the catch location, establishing areas of influence at different ranges around them. Previous to the analysis, prey acoustic estimates were converted into categorical variables. The high number of zeros, the skewed histogram and the few high values were solved by discretization in order to obtain more robust results. For instance, the continuous variable ‘‘Prey” (in m2) were turned into categorical or discrete variables by the groupings: category1 = (Prey = 0); category 2 = (Prey > 0–1); and category 3 = (Prey > 1). Data collected during the 3 years of sampling were used to model the CPUE as a function of SST and prey categories, using Generalized Linear Models (GLMs; Nelder and Wedderburn, 1972). Analyses were performed using the ‘MASS” and ‘‘stats” libraries in the R statistical software (v. 2.7.2., available from the Comprehensive R Archive Network http://cran.r-project.org). Additionally, other statistical methodologies (i.e. Kruskal–Wallis and Chi-square test) were applied to these data, obtaining similar results in all cases (not included in the manuscript). The transformed abundance values, log10 (CPUE + 1), were used to develop the GLMs. Two basic models were chosen:

Table 2 Interannual correlations between tuna CPUE inside and outside the study area and the abundance of anchovies, other pelagics, fluid-like plankton and all prey combined. Signs [(+) or ()] indicate the direction of the correlation. CPUE inside Anchovy Pelagic Fluid-like plankton Total prey

(+) (+) (+) (+)

p = 0.1064, p = 0.1160, p = 0.5295, p = 0.0562,

CPUE outside r2 = 0.9723 r2 = 0.9672 r2 = 0.4538 r2 = 0.9922

() () () ()

p = 0.1316, p = 0.1220, p = 0.7675, p = 0.1818,

r2 = 0.9579 r2 = 0.9637 r2 = 0.1276 r2 = 0.9206

CPUE  as.factor (anchovy) + as.factor (other pelagics) + as.factor (fluid-like) + SST; and CPUE  as.factor (total prey) + SST. Both models were carried out in analysis for each individual year, as well as, for the overall period 2003–2005. GLMs were applied to identify the relationship among individual prey factors, SST and the response variable, the CPUE. We applied a stepwise elimination, based on the Akaike information criteria (AIC) following Venables and Ripley (2002), to determine which explanatory factors to include in each GLM. The use of a GLM prevents the bias associated with the back transformation of a linear model applied to log-transformed CPUE. CPUE being continuous, positive and skewed, the use of GLM also allows considering the role of variables with non-normal distributions and continuous variables and factors together (Stefansson, 1996). 3. Results 3.1. Spatial distribution of albacore tuna and prey In 2003, most albacore tuna catches were located within the standard JUVENA area (Fig. 2), mainly over the Cap Ferret Canyon (Fig. 1) with occasional events occurring on the western part of the Cantabrian shelf break. Anchovies (mainly juvenile) were found distributed in monospecific schools along the shelf-break over the southern part of the Bay of Biscay, between 43°400 and 44°500 N, and between 5° and 1°500 W (Fig. 2a). The amount of fluid-like plankton observed during this survey was very low with sparse patches dispersed over the area (Fig. 2b). Other pelagics were distributed all along the shelf break, closer to the coast in the Cantabrian Sea (Fig. 2c). In 2004, the majority of albacore tuna catches occurred outside the JUVENA coverage area (more than 20 times the amount of

Fig. 5. Significant outputs of the Generalized Linear Model (CPUE  as.factor (anchovy) + as.factor (other pelagics) + as.factor (fluid-like) + SST) at three different scales for the years 2003 and 2005 separately.

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catches that took place inside the coverage area; Fig. 3 and Table 1). Inside the JUVENA coverage area, the catches were located over the shelf break at the edges of the Cap Breton Canyon (Fig. 1). During this year, anchovy was only observed in a small area over the continental shelf-break of the Cantabrian Sea (Fig. 3a); it was distributed in surface isolated schools of juveniles. The distribution of fluid-like plankton was similar to that of anchovies, but extended more toward the coast (Fig. 3b). Other pelagics were located mostly on the shelf, close to the Cantabrian and French coasts (Fig. 3c). In 2005, most of the albacore tuna catches occurred inside the JUVENA area, off the shelf between Cap Breton and Cap Ferret Canyons (Fig. 4). Anchovies (mainly juvenile) were extensively distributed in surface schools, offshore, up to 45°300 N and 4°W (Fig. 4a). Fluid-like plankton were mostly observed around Cap Ferret but also near the Cap Breton Canyon (Fig. 4b). The remainder of the other pelagics were found scattered throughout the JUVENA coverage area (Fig. 4c). 3.2. Abundance estimates and large-scale correlation The overall estimates of relative abundance of prey within the JUVENA area provided different patterns for the three groups that were considered (Table 1). Fluid-like plankton showed a strong increase throughout the 3 years. The abundance of anchovies and other pelagics strongly decreased from 2003 to 2004 (anchovies were virtually absent from the area in 2004) to reach the highest abundance in 2005. Correlation between CPUE and prey abundance inside the JUVENA area was positive (but not significant) with all prey categories (Table 2). This correlation tends to significance (p = 0.056, r2 = 0.99) considering the total amount of prey. A symmetric trend (negative correlation) was observed between CPUE

111

outside the JUVENA area and prey abundance. Although these correlations are based on just 3 years, the trends are remarkably consistent. 3.3. Generalized linear models GLMs could only be applied for 2003 and 2005 because of the lack of CPUE data inside the JUVENA area in 2004. GLMs based on multiple explanatory variables were established and the partial effect of each covariate was plotted and analyzed (Figs. 5–7 and Tables 3 and 4). The categorical and regular fits indicate the effects of each individual variable on CPUE abundance distribution. Data were analyzed at the three local spatial scales (111, 56, and 44km diameter) (see Section 2.3) and only the final models selected after the stepwise process are presented. 3.3.1. Juvena 2003 In 2003, SST had a significantly negative effect on CPUE on all three scales, whatever the model (including prey categories or total prey). The unique prey category was anchovy, which had a significantly positive effect on CPUE on scale 2 (Tables 3 and 4 and Figs. 5 and 6). 3.3.2. Juvena 2005 In 2005, there was no significant effect of SST on CPUE. However, anchovy abundance had a significantly positive effect on CPUE on all three scales. Similar patterns were found for total prey but with the highest significance at scales 2 and 3. The unique covariate presenting a significant negative effect on CPUE was the prey category of other pelagics at scale 3 (Tables 3 and 4 and Figs. 5 and 6). 3.3.3. Juvena 2003–2005 Our results for prey categories and total prey during the period 2003–2005, were the same as in those reported for 2005, although with a higher level of significance. SST had a significant negative effect on CPUE only at scale 3 but having a higher level of significance in the model that included prey categories compared to the model with total prey (Tables 3 and 4 and Fig. 7). 4. Discussion

Fig. 6. Significant outputs of the Generalized Linear Model (CPUE  as.factor (total prey) + SST) at three different scales for the years 2003 and 2005 separately.

In this study, we found that at an interannual scale more albacore tuna CPUE observations occurred inside the JUVENA area when prey were more abundant. However, negative correlations were obtained between albacore tuna CPUE outside the JUVENA area and the prey abundance inside the JUVENA area. These correlations were not significant but this may be because of the limited number of years considered in this study. Yet, due to the high r2 (always > 0.92, except in the case of fluid-like prey, Table 1) we postulate that at an interannual-regional scale, tuna distribution, as inferred by CPUE, is driven by prey distribution. Our results are consistent with other studies that have focused on spatial distribution of tuna at regional scales and that have also established positive correlations with their prey (Sund et al., 1981; Bertrand et al., 2002b). Rose and Leggett (1990) reported that predators tend to congregate where prey is abundant, and mobile prey tends to avoid areas of high predator density. These authors showed that at large scales, predator and prey densities are positively correlated. Analyses at smaller scales showed contrasting results. In 2003, a year characterised by extremely high SST (Fontán et al., 2008; Goikoetxea et al., 2009), the physical environmental conditions had a greater influence on albacore tuna CPUE than biotic variables. This suggests that under extreme environmental conditions, the rela-

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Fig. 7. Significant outputs of the Generalized Linear Models at three different scales considering both years together (2003 and 2005): (a) CPUE  as.factor (anchovy) + as.factor (other pelagics) + as.factor (fluid-like) + SST; (b) CPUE  as.factor (total prey) + SST.

Table 3 Results from multivariate-based GLMs (CPUE  as.factor (anchovy) + as.factor (other pelagics) + as.factor (fluid-like) + SST). For each model, the degrees of freedom (d.f.), the deviance (Dev), the residual degrees of freedom (Resid. d.f.), the residual deviance (Resid. Dev), the F-value, and p-value are given. Signs [(+) or ()] indicate the direction of the correlation. Model Scale 3 2003 2005

2003–2005

Scale 2 2003

2005 2003–2005 Scale 1 2003 2005 2003–2005

NULL SST NULL Anchovy Pelagic NULL Anchovy Pelagic SST NULL Anchovy SST NULL Anchovy NULL Anchovy NULL SST NULL Anchovy NULL Anchovy

d.f.

Dev.

1

2.435

2 2

2.28 1.805

2 1 1

7.48 8.087 3.737

1 1

1.004 1.981

2

2.234

2

4.623

1

2.435

2

1.794

2

3.682

tive importance of physical and biotic constraints may be altered and hence, physical constraints impact albacore tuna dynamics more dramatically than under non-extreme environmental condi-

Resid. d.f.

Resid. Dev.

57 56 109 107 105 173 171 170 169

13.352 10.916 32.882 30.602 28.796 64.115 56.636 48.549 44.812

57 56 55 109 107 173 171

13.351 12.348 10.367 32.882 30.648 64.115 59.492

57 56 109 107 173 171

13.352 10.916 32.882 31.088 64.115 60.433

F-Value

p-Value

12.494

() 0.000827

4.158 3.291

(+) 0.01829 () 0.04108

14.104 30.498 14.092

(+) 2.165e06 () 1.241e07 () 0.0002391

5.881 10.51

(+) 0.01868 () 0.002019

3.899

(+) 0.02318

6.644

(+) 0.001663

12.494

() 0.000827

3.087

(+) 0.04972

5.209

(+) 0.006365

tions. Moreover, our results also suggest that the relationship between albacore tuna and their prey might be decoupled under extreme environmental situations, which would have important

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Table 4 Multivariate-based GLMs, (CPUE  as.factor (total prey) + SST). For each model, the degrees of freedom (d.f.), the deviance (Dev), the residual degrees of freedom (Resid. d.f.), the residual deviance (Resid. Dev), the F-value and p-value are given. Signs [(+) or ()] indicate the direction of the correlation. Model Scale 3 2003 2005 2003–2005

Scale 2 2003 2005 2003–2005 Scale 1 2003 2005 2003–2005

NULL SST NULL Total prey NULL Total prey SST NULL SST NULL Total prey NULL Total prey NULL SST NULL Total prey NULL Total prey

d.f.

Dev.

1

2.435

2

3.311

2 1

9.748 1.984

1

3.659

2

2.993

2

5.478

1

2.435

2

1.867

2

3.475

implications for the dynamics of the Bay of Biscay ecosystem. In fact, in a global climate-warming scenario, extremely warm summers such as the one of 2003 (Fontán et al., 2008; Goikoetxea et al., 2009) could be more frequent. Changes in SST could have an impact on both predator and prey spatial distributions, according to relative habitat preferences. This might affect their overlap and the degree of predation by albacore tuna on their prey. Different food availability encountered during feeding migrations in their first years of life might influence the overall condition of the juvenile albacore tuna population. However, natural mortality of prey populations would also be affected under varying degrees of predation pressure. Albacore tuna CPUE were positively correlated with anchovy abundance and total prey abundance in 2005, and throughout the 3 years taken as a whole (Tables 3 and 4) suggesting that anchovies constitute a key target for albacore tuna in the southern part of the Bay of Biscay, at least during the study period. There are several possible explanations for this relationship. First, anchovies are generally abundant in autumn in the study area (Boyra and Uriarte, 2006; Boyra et al., 2006). Actually, albacore tuna approach the continental slope of the Bay of Biscay at the same time when a large part of juvenile anchovy population is occupying the offshore pelagic area before migrating to shallow coastal waters (Koutsikopoulos and Le Cann, 1996; Boyra and Uriarte, 2006; Boyra et al., 2006; Irigoien et al., 2007, 2008). Second, anchovies distributed in this area during this period are predominantly juveniles; an easy to catch prey compared to the larger and faster-moving species that share the area (such as sardines Sardina pilchardus, sprats Sprattus sprattus, mackerel Scomber scombrus and horse mackerel Trachurus trachurus). In addition, juvenile anchovies are usually found in aggregations of dense schools that are attractive for tuna. Finally, they are more nutritious (Becker et al., 2007) and abundant than fluid-like plankton, the other slow-swimming prey species available at this time; thus, they are ideal to meet the strong metabolic demands of tuna (Sund et al., 1981; Graham and Laurs, 1982). The concurrence of these factors may make anchovies an energetically efficient prey for albacore tuna compared to other potential prey present within this area at this period. These results are supported by stomach-content analyses of albacore tuna (Goñi, 2008) that showed that anchovies were by far the most

Resid. d.f.

Resid. Dev.

57 56 109 107 173 171 170

13.352 10.916 32.882 29.571 64.115 54.367 52.383

57 55 109 107 173 171

13.352 9.233 32.882 29.889 64.115 58.638

57 56 109 107 173 171

13.352 10.916 32.882 31.015 64.115 60.64

F-Value

p-Value

12.494

() 0.000827

5.991

(+) 0.003419

15.818 6.439

(+) 5.01e07 () 0.012060

21.798

() 1.99e05

5.358

(+) 0.00606

7.987

(+) 0.0004829

12.494

() 0.000827

3.221

(+) 0.0438

4.899

(+) 0.008526

important prey of tuna in the Bay of Biscay during this time period, accounting for more than 86% in wet weight. Although we only considered 3 years of data and there was a rather short survey period (25 days from late September to early October), our results are promising and should be investigated further. We recommend that the study period also be expanded to the other summer months when albacore tuna enter the Bay of Biscay to test whether the preference for anchovies is constant or restricted to the period when the juveniles form large schools. The survey was designed to assess anchovy abundance and distribution and not to study the interaction between tuna CPUE and prey abundance; however, the use of acoustic data recorded by commercial tuna vessels operating in the Bay of Biscay could be an opportunity to complement scientific data (ICES, 2007). Acknowledgements This work was supported by the JUVENA project funded by the Department of Agriculture and Fisheries of the Basque Government and the Ministry of Agriculture, Fishery and Food (MAPA), of the Spanish Government and a Grant to AL. (Technological Centre Foundation). We would like to thank all the skippers that kindly provided their logbooks and the crews of the commercial fishing vessels that took part in the JUVENA cruises. We are also grateful to the technical staff of AZTI (Carlota Perez, Iñaki Rico) for their help in the data processing and analyses, especially to Udane Martinez. I wish to thank Drs. M. Woillez and F. Dufour for their advices during this work. We would also like to express our gratitude to Dr. Xabier Irigoien and Andres Uriarte (AZTI) for their invaluable discussions. M. Kensington is thanked for revising the English in this manuscript. This paper is contribution No. 462 from AZTI-TECNALIA (Marine and Food Research). References Albaina, A., Irigoien, X., 2004. Relationships between frontal structures and zooplankton communities along a cross shelf transect in the Bay of Biscay (1995 to 2003). Marine Ecology Progress Series 284, 65–75. Albaina, A., Irigoien, X., 2007. Fine scale zooplankton distribution in the Bay of Biscay in spring 2004. Journal of Plankton Research 29, 851–870.

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